• Communications for Statistical Applications and Methods
• /
• v.23 no.2
• /
• pp.147-161
• /
• 2016

This paper introduces the four parameter new generalized inverse Weibull distribution and investigates the potential usefulness of this model with application to reliability data from engineering studies. The new extended model has upside-down hazard rate function and provides an alternative to existing lifetime distributions. Various structural properties of the new distribution are derived that include explicit expressions for the moments, moment generating function, quantile function and the moments of order statistics. The estimation of model parameters are performed by the method of maximum likelihood and evaluate the performance of maximum likelihood estimation using simulation.

• Communications for Statistical Applications and Methods
• /
• v.21 no.2
• /
• pp.193-200
• /
• 2014

It was recognized by some researchers that the disturbance variance in a censored regression model is frequently underestimated by the maximum likelihood method. This underestimation has implications for the estimation of marginal effects and asymptotic standard errors. For instance, the actual coverage probability of the confidence interval based on a maximum likelihood estimate can be significantly smaller than the nominal confidence level; consequently, a Bayesian estimation is considered to overcome this difficulty. The behaviors of the maximum likelihood and Bayesian estimators of disturbance variance are examined in a fixed effects panel regression model with a limited dependent variable, which is known to have the incidental parameter problem. Behavior under random effect assumption is also investigated.

• The Korean Journal of Applied Statistics
• /
• v.4 no.1
• /
• pp.13-24
• /
• 1991

This paper presents a Monte Carlo evaluation of estimators for nonlinear consored simultaneous equations models. We examine the performance of the maximum likelihood estimator (MLE), the two-step quasi maximum likelihood estimator (2QMLE) proposed by Lee and Hurd (1989), and another quasi MLe using least squares at the first step (LSAE) under varying degrees of freedom and underlying distributions, Although QMLE's are not necessarily consistent, the Monte Carlo results show that the 2QMLE may be used as an alternative to MLE when MLE is not applicable in practice.

• Communications for Statistical Applications and Methods
• /
• v.20 no.1
• /
• pp.63-75
• /
• 2013

In this paper, we derive maximum likelihood estimators (MLEs) and approximate maximum likelihood estimators (AMLEs) of unknown parameters in a generalized half logistic distribution under Type-II hybrid censoring. We also obtain approximate confidence intervals using asymptotic variance and covariance matrices based on the MLEs and the AMLEs. As an illustration, we examine the validity of the proposed estimation using real data. Finally, we compare the proposed estimators in the sense of the mean squared error (MSE), bias, and length of the approximate confidence interval through a Monte Carlo simulation for various censoring schemes.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.4
• /
• pp.747-749
• /
• 2017

In this paper, we propose a novel precoder selection technique for maximum-likelihood (ML) detected spatially multiplexed multiple-input multiple-output (MIMO) systems. Previous precoder selection techniques were designed without considering UEP, however the proposed technique is designed considering multi-antenna unequal error protection (UEP). Simulations demonstrate the improved multi-antenna UEP performance by the proposed technique.

• Communications for Statistical Applications and Methods
• /
• v.20 no.5
• /
• pp.405-416
• /
• 2013

This paper develops a maximum profile likelihood estimator of unknown parameters of the exponentiated Gumbel distribution based on upper record values. We propose an approximate maximum profile likelihood estimator for a scale parameter. In addition, we derive Bayes estimators of unknown parameters of the exponentiated Gumbel distribution using Lindley's approximation under symmetric and asymmetric loss functions. We assess the validity of the proposed method by using real data and compare these estimators based on estimated risk through a Monte Carlo simulation.

• Journal of Communications and Networks
• /
• v.15 no.3
• /
• pp.245-251
• /
• 2013

This paper addresses the issue of time-difference-of-arrival (TDOA) estimation for complex noncircular signals. First, under the wide-sense stationary assumption, we derive the maximum likelihood (ML) estimator and the Cramer-Rao lower bound for Gaussian noncircular signals in Gaussian circular noise. The ML estimator uses the second-order statistics information of a noncircular signal more comprehensively when compared with the cross-correlation (CC) and the conjugate CC estimators. Further, we present a scheme to modify the traditional signal-selective TDOA methods for noncircular signals on the basis of the cyclostationarity of man-made signals. This scheme simultaneously exploits the information contained in both the cyclic cross-correlation (CCC) and the conjugate CCC of a noncircular signal.

• International Journal of Reliability and Applications
• /
• v.13 no.2
• /
• pp.91-104
• /
• 2012

Sarhan and Kundu (2009) introduced a new distribution named as the generalized linear failure rate distribution. This distribution generalizes several well known distributions. The probability density function of the generalized linear failure rate distribution can be right skewed or unimodal and its hazard function can be increasing, decreasing or bathtub shaped. This distribution can be used quite effectively to analyze lifetime data in place of linear failure rate, generalized exponential and generalized Rayleigh distributions. In this paper, we apply the simulated annealing algorithm to obtain the maximum likelihood point estimates of the parameters of the generalized linear failure rate distribution. Simulated annealing algorithm can not only find the global optimum; it is also less likely to fail because it is a very robust algorithm. The estimators obtained using simulated annealing algorithm have been compared with the corresponding traditional maximum likelihood estimators for their risks.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.1C
• /
• pp.110-116
• /
• 2008

Maximum likelihood(ML) diretion-of-arrival(DOA) estimation is essentially optimization of multivariable nonlinear cost function. Since the final estimate is highly dependent on the initial estimate, an initialization is critical in nonlinear optimization. We propose a multi-dimensional(M-D) search scheme of uniform exhaustive search and improved exhaustive search. Improved exhaustive search is superior to uniform exhaustive search in terms of the computational complexity and the accuracy of the estimates.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.3
• /
• pp.633-641
• /
• 2014

The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.